Handwriting recognition is a widely implemented technology to electronically identify handwritten text. In online handwriting recognition, text written on a touch surface of an electronic touch device is dynamically recognized based on the movements of a writing device (digital pen, a finger, or a stylus) and presented to the user after each continuous stroke such as a character or word is entered. Therefore, the user is able to edit a character or a word in the event of incorrect recognition of text by the electronic device as soon as it is presented to the user. On the other hand, in offline handwriting recognition, recognition of characters occurs by identifying characters from an image of handwritten text instead of the user writing on a touch surface. Here, the recognized text is presented to a user only when the entire handwritten text represented in the image is recognized.
One challenge associated with offline handwriting recognition is that the handwritten text cannot be edited or re-entered by the user until the entire handwritten text is recognized. A user, thus, may not be able to provide a feedback for correction after the recognition of each character or word in case of an incorrect recognition of that character or word. Thus, the errors in the offline handwriting recognition of that handwritten text may keep on accumulating in the absence of user supervision. Therefore, it is desirable to increase the accuracy of recognition of handwritten text in systems that implement offline handwriting recognition.
Another challenge is that various users write in varied handwriting styles and in different languages. Each character in the handwritten text may have been written in multiple handwriting styles by different users. It is desirable that a character be correctly recognized in spite of having been written in varied handwriting styles. In addition, a character in one language may be similar, but not same, to a character of a different language and is, thus, prone to be incorrectly recognized. Therefore, there is need for greater accuracy in offline handwriting recognition of such handwritten text.